ZigZag - Deep Learning Hardware Design Space Exploration
This repository presents the novel version of our tried-and-tested hardware Architecture-Mapping Design Space Exploration (DSE) Framework for Deep Learning (DL) accelerators. ZigZag bridges the gap between algorithmic DL decisions and their acceleration cost on specialized accelerators through a fast and accurate hardware cost estimation.
VisualizationStage Class Reference

Class that passes through all results yielded by substages, and saves the visualizations of configurations and results. More...

Inheritance diagram for VisualizationStage:
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Public Member Functions

def __init__ (self, list[StageCallable] list_of_callables, *str dump_folder, **Any kwargs)
 
def run (self)
 
- Public Member Functions inherited from Stage
def __init__ (self, list["StageCallable"] list_of_callables, **Any kwargs)
 
def __iter__ (self)
 
bool is_leaf (self)
 

Public Attributes

 dump_folder
 
 loop_ordering_file
 
 figure_is_saved
 
- Public Attributes inherited from Stage
 kwargs
 
 list_of_callables
 

Detailed Description

Class that passes through all results yielded by substages, and saves the visualizations of configurations and results.

Constructor & Destructor Documentation

◆ __init__()

def __init__ (   self,
list[StageCallable list_of_callables,
*str  dump_folder,
**Any  kwargs 
)
Parameters
dump_folderOutput folder for dumps
kwargsany kwargs, passed on to substages

Member Function Documentation

◆ run()

def run (   self)

Reimplemented from Stage.

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Member Data Documentation

◆ dump_folder

dump_folder

◆ figure_is_saved

figure_is_saved

◆ loop_ordering_file

loop_ordering_file

The documentation for this class was generated from the following file: